{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_trajectory(transforms_path, ax, color='r', size=20, interval=1, view_num=1):\n",
    "    plt.style.use('seaborn-whitegrid')\n",
    "    legend_flag = False\n",
    "    \n",
    "\n",
    "    with open(transforms_path) as json_file:\n",
    "        contents = json.load(json_file)\n",
    "        fovx = contents[\"camera_angle_x\"]\n",
    "        frames = contents[\"frames\"]\n",
    "        delta = 0.0\n",
    "        cnt = 0\n",
    "        pre_pos = None\n",
    "        pos_list = []\n",
    "\n",
    "        for idx, frame in enumerate(frames):\n",
    "            if idx % (interval * view_num) != 0:\n",
    "                continue\n",
    "            file_path = os.path.split(frame['file_path'])[-1]\n",
    "            # transform a to list\n",
    "            c2w = np.array(frame['transform_matrix'])\n",
    "\n",
    "            pos = c2w[:3, 3]  # camera center position\n",
    "            pos_list.append(pos)\n",
    "            x_dir = c2w[:3, 0]\n",
    "            y_dir = c2w[:3, 1]\n",
    "            z_dir = c2w[:3, 2]\n",
    "\n",
    "            x_head_width = size * np.linalg.norm(x_dir[:2]) / 2\n",
    "            z_head_width = size * np.linalg.norm(z_dir[:2]) / 2\n",
    "\n",
    "            ax.arrow(pos[0], pos[1], size * x_dir[0], size * x_dir[1], color='r', head_width=x_head_width, label='x-axis')\n",
    "            # ax.arrow(pos[0], pos[1], size * y_dir[0], size * y_dir[1], color='g', head_width=size/2, label='y-axis')\n",
    "            ax.arrow(pos[0], pos[1], size * z_dir[0], size * z_dir[1], color='b', head_width=z_head_width, label='z-axis')\n",
    "            if not legend_flag:\n",
    "                ax.legend()\n",
    "                legend_flag = True\n",
    "            \n",
    "            if pre_pos is None:\n",
    "                pre_pos = pos\n",
    "            else:\n",
    "                delta += np.linalg.norm(pos - pre_pos)\n",
    "                cnt += 1.0\n",
    "                pre_pos = pos\n",
    "\n",
    "    base_step = delta / cnt / interval\n",
    "    print('Average step length: {:.2f}/{:.2f}m'.format(base_step * interval, base_step))\n",
    "    print('Total images: {}/{}'.format(int(cnt), len(frames)))\n",
    "\n",
    "    pos_list = np.array(pos_list)\n",
    "    min_pos = np.min(pos_list, axis=0)\n",
    "    max_pos = np.max(pos_list, axis=0)\n",
    "    print('Min position: {}'.format(min_pos))\n",
    "    print('Max position: {}'.format(max_pos))\n",
    "\n",
    "    ax.axis('equal')\n",
    "    ax.set_xlabel('x/m')\n",
    "    ax.set_ylabel('y/m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average step length: 19.29/19.29m\n",
      "Total images: 69/70\n",
      "Min position: [-1180.53      88.6456    75.63  ]\n",
      "Max position: [-1089.98    222.993    75.63 ]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# data_path, subset = '../data/UE-collected', 'vehicle-train-20231114'\n",
    "transforms_path = os.path.join('../data/UE-collected/aerial/block2_20_cam/transforms_train.json')\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "draw_trajectory(transforms_path, ax, color='r', size=5, interval=1, view_num=1)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
